Lecture notes in physics

Special relativity is one of the high points of the undergraduate mathematical physics syllabus. Nick Woodhouse writes for those approaching the subject with a background in mathematics: he aims to build on their familiarity with the foundational material and the way of thinking taught in first-year mathematics courses, but not to assume an unreasonable degree of prior knowledge of traditional areas of physical applied mathematics, particularly electromagnetic theory. His book provides mathematics students with the tools they need to understand the physical basis of special relativity and leaves them with a confident mathematical understanding of Minkowski's picture of space-time. Special Relativity is loosely based on the tried and tested course at Oxford, where extensive tutorials and problem classes support the lecture course. This is reflected in the book in the large number of examples and exercises, ranging from the rather simple through to the more involved and challenging. The author has included material on acceleration and tensors, and has written the book with an emphasis on space-time diagrams. Written with the second year undergraduate in mind, the book will appeal to those studying the 'Special Relativity' option in their Mathematics or Mathematics and Physics course. However, a graduate or lecturer wanting a rapid introduction to special relativity would benefit from the concise and precise nature of the book.

This book gives a synthesis of the state of the art in artificial intelligence in astronomy and astrophysics, presents its current applications and points out directions of future work. The individual chapters report on the application of artificial intelligence techniques for large astronomical surveys, for processing cosmic ray data, for facilitating data reduction using image processing systems, for telescope scheduling, for observatory ground support operations, for observation proposal preparation assistance, and for scientific applications such as stellar spectral and galaxy morphology classification. The new field of connectionism (neural networks) is also surveyed. The book is designed to be self-contained: a glossary of terms used in this area is provided and an index of terms, acronyms and proper names completes the book.